Prediction of the Risk of Severe COVID-19 in Patients with Proximal Femural Fractures (Literature Review)

Bekzat Beisenov, Aida Omarova

2023

Data confidence 70 medium

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It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Predicting the severity of COVID-19 in patients with hip fractures is of great importance, as this category of patients is particularly vulnerable and often has additional risk factors such as older age, comorbidities, and reduced mobility. Accordingly, the risk of developing a severe form of COVID-19 in such patients is higher, which can lead to an increase in mortality and complications. The aim of the current review is to find methods for predicting the severity of the course of coronavirus infection in patients with hip fractures.The review included publications on methods for predicting the course of coronovirus infection in patients with traumatological pathology. Separately, cases with fractures of the proximal femur were considered.The search strategy included the use of the MeSH system and the keywords “hip fracture”, “coronavirus infection”, OR “COVID 19” AND “proximal femur fracture”.All citations were formatted using EndNote X6 software (Clarivate Analytics, New York, USA). Restrictions on the year of publication of articles were not applied.Key words: hip fracture, coronavirus infection, COVID 19, fracture of the proximal femur.